Object detection (OD) is a crucial computer vision task that has seen the development of
many algorithms and models over the years. While the performance of current OD models …

In this paper, we delve into two key techniques in Semi-Supervised Object Detection
(SSOD), namely pseudo labeling and consistency training. We observe that these two …

Extrinsic parameter calibration is the foundation and prerequisite for LiDAR and camera
data fusion of the autonomous system. This technology is widely used in fields such as …

We introduce a new image segmentation task, called Entity Segmentation (ES), which aims
to segment all visual entities (objects and stuffs) in an image without predicting their …

Recent camouflaged object detection (COD) attempts to segment objects visually blended
into their surroundings, which is extremely complex and difficult in real-world scenarios …

Despite substantial progress in 3D object detection, advanced 3D detectors often suffer from
heavy computation overheads. To this end, we explore the potential of knowledge distillation …

Intelligent video surveillance is an important computer vision application in natural
environments. Since detected objects under surveillance are usually low-resolution and …

Target detection is a revolutionary advancement in computer vision that provides the ability
to identify specific targets in images for a wide variety of applications, including but not …

Dense image segmentation tasks eg, semantic, panoptic) are useful for image editing, but
existing methods can hardly generalize well in an in-the-wild setting where there are …

Despite the promising development of Automatic Visual Inspection (AVI) in the
manufacturing industry, detecting small-sized defects with fewer pixels coverage remains a …